关键词: 复杂网络，社团结构，SNN相似度矩阵，谱评分法，FCM算法

Abstract: Based on the improved SNN similarity matrix and spectral bisection method, this paper proposed a new algorithm for detecting the community structure in complex networks. The improved SNN similarity matrix was firstly computed and normalized and its cigenvalucs and cigenvectors were obtained subsequently. hhen different numbers of the first non-trivial eigenvectors were chosen as clustering samples, FCM algorithm began to work and the corresponding modularity was computed. The best structure of the network was detected by mapping the largest value of modularity.The experiment shows the validity of the presented method The result obtained here is compared with other popular ones and the conclusion is that the accuracy of the results calculated by this approach is much better than the known ones.

Key words: Complex networks, Community structure, SNN similarity matrix, Spectral bisection method, FCM algorithm